Search Results - (( parameter optimization _ algorithm ) OR ( framework implementation model algorithm ))

Perovskite lattice constant prediction framework using optimized artificial neural network and fuzzy logic models by metaheuristic algorithms by Bouzateur, Inas, Ouali, Mohammed Assam, Bennacer, Hamza, Ladjal, Mohamed, Khmaissia, Fadoua, Rahman, Mohd Amiruddin Abd, Boukortt, Abdelkader

“…The identification of optimized parameters for the ANN and fuzzy logic models is accomplished using innovative metaheuristic algorithms such as, Particle Swarm Optimization (PSO), Invasive Weed Optimization (IWO) and Imperialist Competitive Algorithm (ICA). …”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohammad Fadhil, Abas, Bayuaji, Luhur

“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Ayop Azmi, Nurnajmin Qasrina Ann, Pebrianti, Dwi, Abas, Mohammad Fadhil, Bayuaji, Luhur

“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…A voltage stability index-based approach was adopted to establish the optimal locations of the DGs in the system. Initially, the Particle Swarm Optimization was implemented to establish the optimal sizes of DGs and the performance of the implemented algorithm was analyzed and quantified. …”

Optimization of balanced academic curriculum problem in educational institutions using teaching learning based optimization algorithm by Mohd Fadzil Faisae, Ab Rashid, Wasif, Ullah

“…This study aims to optimize BACP using the Teaching-Learning Based Optimization (TLBO) algorithm, addressing the limitations of existing approaches and providing an efficient framework for curriculum balancing. …”
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Optimization of operating cost and energy consumption in a smart grid by Mahdi, Baqer Saleh, Sulaiman, Nasri, Shehab, Mohanad Abd, Shafie, Suhaidi, Hizam, Hashim, Mohd Hassan, Siti Lailatul

“…The study presents three scenarios illustrating the optimal operational values for various parameters and energy consumption, providing a comprehensive analysis of the proposed algorithm's efficacy. …”
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Collision avoidance mechanisms using artificial potential field for UAVs by Abdul Azis, Fadilah, Tan, Jie Sim, Md Ghazaly, Mariam, Mohamad Hanif, Noor Hazrin Hany

“…This research demonstrates the APF algorithm’s robustness and practical applicability while identifying limitations related to environmental adaptability and the need for parameter optimization in more complex flight conditions.…”
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Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs by Liew, W.S., Seera, M., Loo, C.K., Lim, E.

“…Speciation was implemented using subset selection of classification data attributes, as well as using an island model genetic algorithms method. …”
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A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks by , Abdul Wahid, Khan, Adnan Umar, , Mukhtarullah, Khan, Sheroz, Shah, Jawad

“…In this work we implement the framework for multi layered version of CSC with incorporation of pooling operations applied on real images and analyze the performance of resulting model. …”
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Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

“…The successful validation in real-world systems marks a significant milestone, showing that the SPM technique can significantly improve model optimization in diverse and practical contexts . …”
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Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics by Zamani, Abu Sarwar, Hassan Abdalla Hashim, Aisha, Shatat, Abdallah Saleh Ali, Akhtar, Md. Mobin, Rizwanullah, Mohammed, Mohamed, Sara Saadeldeen Ibrahim

“…In the reduction phase, the optimal features are selected with theaid of the developed Hybrid Flower Pollination Bumblebees Optimization Algorithm (HFPBOA). …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…It is organized into three phases: preliminary investigation, implementation and analysis, and validation. The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

“…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

“…This type of outcome is valuable to the decision-maker to implement a more optimal strategy for reducing the probability of landslides and its associated damages. ? …”

Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam by Rustam, Ilham

“…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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Dynamic investment model for the restructed power market in the presence of wind source by Esfahani, Mohammad Tolou Askari Sedehi

“…The proposed framework has been implemented in the hypothetical restructured power market using the IEEE Reliability Test System. …”
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Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan by Ahmat Ruslan, Fazlina

“…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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